Posterior Circulation Mechanical Thrombectomy through Primitive Trigeminal Artery: A Case Report

Introduction: Primitive trigeminal artery (PTA) is a rare intracranial vascular malformation, and mechanical thrombectomy and revascularization via PTA are rarely reported. Case Presentation: We reported a case of mechanical thrombectomy through PTA in a patient who presented with sudden slurred speech and had a National Institutes of Health Stroke Scale score of 12. Digital subtraction angiography of the cerebral vasculature showed PTA formation in the right internal carotid artery cavernous segment, with acute occlusion of the distal basilar artery at the PTA junction, and bilateral vertebral arteries and proximal basilar artery were underdeveloped. Therefore, we chose mechanical thrombectomy via PTA, but unfortunately, the vessel failed to recanalize. Follow-up at 1-month post-procedure indicated that the patient had passed away. We present the endovascular process and analyze and summarize the reasons for the failure to provide a reference for subsequent mechanical thrombectomy via PTA. Conclusions: PTA increases the risk of ischemic stroke and adds to the complexity of mechanical thrombectomy post-stroke. However, in certain situations, PTA can be used as a thrombectomy channel to increase the first-line possibility of timely endovascular treatment to save ischemic brain tissue

Inorganic Nitrogen Uptake Characteristics of Three Typical Bloom-Forming Algae in the East China Sea

Inorganic nitrogen (N) is an important element for eutrophication and harmful algal bloom (HAB) formation. However, the roles of inorganic N in HAB outbreaks are still unclear. Here, we compared the affinities and abilities for inorganic N uptake and assimilation among three typical bloom-forming algae in the East China Sea (ECS), Skeletonema costatum, Prorocentrum donghaiense and Alexandrium pacificum by investigating the uptake and enzymatic (nitrate reductase (NR) and glutamine synthetase (GS) kinetics for nitrate and ammonia. The Ks of nitrate and ammonium in S. costatum was lower than those in P. donghaiense and A. pacificum. The NR activity of S. costatum and P. donghaiense exhibited a positive relationship with the nitrate concentration, and NR activity of S. costatum was nearly 4-fold higher than that of P. donghaiense at high nitrate concentration. However, the NR activity of A. pacificum could not be detected. The GS activity of three species decreased with the increase of ammonium concentrations, and the highest GS activity was detected in A. pacificum. S. costatum presented the highest affinity for nitrate and ammonium, followed by P. donghaiense and A. pacificum. Moreover, P. donghaiense exhibited the highest affinity for intracellular ammonium. Our results characterized the differences in inorganic nitrogen uptake among the three typical bloom-forming algae, which may contribute to the formation of blooms in the coastal waters of the ECS

The Effect of Magnetic Resonance Imaging Based Radiomics Models in Discriminating stage I–II and III–IVa Nasopharyngeal Carcinoma

Background: Nasopharyngeal carcinoma (NPC) is a common tumor in China. Accurate stages of NPC are crucial for treatment. We therefore aim to develop radiomics models for discriminating early-stage (I–II) and advanced-stage (III–IVa) NPC based on MR images. Methods: 329 NPC patients were enrolled and randomly divided into a training cohort (n = 229) and a validation cohort (n = 100). Features were extracted based on axial contrast-enhanced T1-weighted images (CE-T1WI), T1WI, and T2-weighted images (T2WI). Least absolute shrinkage and selection operator (LASSO) was used to build radiomics signatures. Seven radiomics models were constructed with logistic regression. The AUC value was used to assess classification performance. The DeLong test was used to compare the AUCs of different radiomics models and visual assessment. Results: Models A, B, C, D, E, F, and G were constructed with 13, 9, 7, 9, 10, 7, and 6 features, respectively. All radiomics models showed better classification performance than that of visual assessment. Model A (CE-T1WI + T1WI + T2WI) showed the best classification performance (AUC: 0.847) in the training cohort. CE-T1WI showed the greatest significance for staging NPC. Conclusion: Radiomics models can effectively distinguish early-stage from advanced-stage NPC patients, and Model A (CE-T1WI + T1WI + T2WI) showed the best classification performance